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A Julia machine learning framework.
A simple Machine Learning Framework written in Swift. Currently features Simple Linear Regression, Polynomial Regression, and Ridge Regression.
No need to keep checking your training, just one import line and you'll know the second it's done.
MLX is an array framework for machine learning on Apple silicon, developed by Apple machine learning research.
A library consisting of useful tools for data science and machine learning tasks.
A modular active learning framework for Python, built on top of scikit-learn.
Visual testing tool for MCP servers.
OpenAI compatible API for LLMs and embeddings (LLaMA, Vicuna, ChatGLM and many others).
Global, black box optimization engine for real world metric optimization by Yelp.
List of molecular design using Generative AI and Deep Learning.
Montague is a semantic parsing library for Scala with an easy-to-use DSL.
CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms.
Llama3 implementation one matrix multiplication at a time.
Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].
A PyTorch implementation of DeepDream.
A parallel neural net microframework.
A PyTorch implementation of Justin Johnson's neural-style (neural style transfer).
Machine learning for NeuroImaging in Python.
A Julia package for non-negative matrix factorization.
Nn builder is a python package that lets you build neural networks in 1 line.
This package provides graphical computation for nn library in Torch7.
An open source AutoML toolkit for automate machine learning lifecycle.
A completely unstable and experimental package that extends Torch's builtin nn library.